10 citations · 27 across the 16 of their papers we have counts for
5 papers · 1 filter
Robust Learning via Conditional Prevalence Adjustment
Minh Nguyen, Alan Q. Wang, Heejong Kim +1
Healthcare data often come from multiple sites in which the correlations between confounding variables can vary widely. If deep learning models exploit these unstable correlations,…
A Framework for Interpretability in Machine Learning for Medical Imaging
Alan Q. Wang, Batuhan K. Karaman, Heejong Kim +4
Interpretability for machine learning models in medical imaging (MLMI) is an important direction of research. However, there is a general sense of murkiness in what interpretabilit…
Learning Invariant Representations with a Nonparametric Nadaraya-Watson Head
Alan Q. Wang, Minh Nguyen, Mert R. Sabuncu
Machine learning models will often fail when deployed in an environment with a data distribution that is different than the training distribution. When multiple environments are av…
A Robust and Interpretable Deep Learning Framework for Multi-modal Registration via Keypoints
Alan Q. Wang, Evan M. Yu, Adrian V. Dalca +1
We present KeyMorph, a deep learning-based image registration framework that relies on automatically detecting corresponding keypoints. State-of-the-art deep learning methods for r…
Neural Pre-Processing: A Learning Framework for End-to-end Brain MRI Pre-processing
Xinzi He, Alan Wang, Mert R. Sabuncu
Head MRI pre-processing involves converting raw images to an intensity-normalized, skull-stripped brain in a standard coordinate space. In this paper, we propose an end-to-end weak…